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Published on: December 19, 2017
APT MRI Signature for Risk Stratification of Pediatric Medulloblastoma
Zhipeng Shen1, Junjie Wen2,3, Xiaohui Ma3
1Department of Neurosurgery, Children's Hospital, Zhejiang University School of Medicine, Hangzhou 310052, Zhejiang, China.
Abstract:
Medulloblastoma (MB), a malignant intracranial tumor, is classified into four molecular subgroups (WNT, SHH, Group 3, Group 4) with distinct risk profiles. This study aimed to establish APT MRI-based radiomic signature for distinguishing risk subgroups of pediatric MB. From February 2018 to May 2023, 72 diagnosed pediatric MB patients were enrolled, all undergoing brain MRI examinations. Radiomic features were extracted from regions of interest in APT-related metric maps and structural MR images, and were subject to a feature selection process. The performance of retained individual features and radiomic signatures generated via the least absolute shrinkage and selection operator (LASSO) was assessed using receiver operating characteristic (ROC) analysis. Final analysis included 56 subjects (mean age: 76.5 ± 41.9 months; 37 males), consisting of 7 WNT, 17 SHH, 9 Group 3, and 23 Group 4 cases. The optimal individual radiomic feature exhibited an area under the ROC curve (AUC) of 0.83 for risk stratification, while the APT-based radiomic signature achieved a higher AUC of 0.86. Notably, structural images and clinical factors failed to provide additional value to the APT-based signature for risk stratification. In conclusion, APT MRI-based radiomic signature demonstrated favorable performance in distinguishing risk groups of pediatric MB, offering valuable insights for clinical diagnosis of MB.
Insights
This study developed an advanced MRI radiomic signature to differentiate pediatric medulloblastoma (MB) risk groups. The new APT MRI-based signature shows promise for improving clinical diagnosis of this brain tumor.
Area of Science:
- Neuro-oncology
- Medical imaging
- Radiomics
Background:
- Medulloblastoma (MB) is a malignant brain tumor with four molecular subgroups (WNT, SHH, Group 3, Group 4) that have different prognoses.
- Accurate risk stratification is crucial for tailoring treatment strategies in pediatric MB.
Purpose of the Study:
- To develop and validate an Amino-Proton Transfer (APT) MRI-based radiomic signature for distinguishing between the molecular risk subgroups of pediatric medulloblastoma.
- To assess the performance of this signature compared to individual radiomic features and conventional imaging/clinical data.
Main Methods:
- Radiomic features were extracted from APT-related metric maps and structural MRI scans of 56 pediatric medulloblastoma patients.
- Feature selection was performed, and radiomic signatures were generated using the least absolute shrinkage and selection operator (LASSO) method.
- Receiver operating characteristic (ROC) analysis was used to evaluate the performance of individual features and the radiomic signature for risk stratification.
Main Results:
- The optimal individual radiomic feature achieved an area under the ROC curve (AUC) of 0.83 for risk stratification.
- The developed APT MRI-based radiomic signature demonstrated a higher AUC of 0.86 in distinguishing medulloblastoma risk groups.
- Incorporating structural MRI data or clinical factors did not improve the diagnostic performance of the APT-based radiomic signature.
Conclusions:
- An APT MRI-based radiomic signature is effective for differentiating pediatric medulloblastoma risk subgroups.
- This radiomic approach offers valuable, non-invasive insights for improving the clinical diagnosis and management of medulloblastoma.
- The findings suggest that APT MRI radiomics can serve as a powerful tool in the precision medicine approach to pediatric brain tumors.
